Developing and debugging

Modal makes it easy to run apps in the cloud, try code changes in the cloud, and debug remotely executing code as if it were right there on your laptop. To speed boost your inner dev loop, this guide provides a rundown of tools and techniques for developing and debugging software in Modal.

Interactivity

You can launch a Modal App interactively and have it drop you right into the middle of the action, at an interesting callsite or the site of a runtime detonation.

Interactive functions

It is possible to start the interactive Python debugger or start an IPython REPL right in the middle of your Modal App.

To do so, you first need to run your App in “interactive” mode by using the --interactive / -i flag. In interactive mode, you can establish a connection to the calling terminal by calling interact() from within your function.

For a simple example, you can accept user input with the built-in Python input function:

@app.function()
def my_fn(x):
    modal.interact()

    print("Enter a number:", end=" ")
    x = input()
    print(f"Your number is {x}")

Now when you run your app with the --interactive flag, you’re able to send inputs to your app, even though it’s running in a remote container!

modal run -i guess_number.py
Enter a number: 5
Your number is 5

For a more interesting example, you can pip_install("ipython") and start an IPython REPL dynamically anywhere in your code:

@app.function()
def f():
    model = expensive_function()
    # play around with model
    modal.interact()
    import IPython
    IPython.embed()

The built-in Python debugger can be initiated with the language’s breakpoint() function. For convenience, breakpoints call interact automatically.

@app.function()
def f():
    x = "10point3"
    breakpoint()
    answer = float(x)

Debugging Running Containers

Debug Shells

Modal also lets you run interactive commands on your running Containers from the terminal — much like ssh-ing into a traditional machine or cloud VM.

To run a command inside a running Container, you first need to get the Container ID. You can view all running Containers and their Container IDs with modal container list.

After you obtain the Container ID, you can connect to the Container with modal shell [container-id]. This launches a “Debug Shell” that comes with some preinstalled tools:

• vim
• nano
• ps
• strace
• curl
• py-spy
• and more!

You can use a debug shell to examine or terminate running processes, modify the Container filesystem, run commands, and more. You can also install additional packages using your Container’s package manager (ex. apt).

Note that debug shells will terminate immediately once your Container has finished running.

modal container exec

You can also execute a specific command in a running Container with modal container exec [container-id] [command...]. For example, to see what files are in /root, you can run modal container exec [container-id] ls /root.

❯ modal container list
                         Active Containers in environment: nathan-dev
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┓
┃ Container ID                  ┃ App ID                    ┃ App Name ┃ Start Time           ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━┩
│ ta-01JK47GVDMWMGPH8MQ0EW30Y25 │ ap-FSuhQ4LpvNAt5b6mKi1CDw │ my-app   │ 2025-02-02 16:02 EST │
└───────────────────────────────┴───────────────────────────┴──────────┴──────────────────────┘

❯ modal container exec ta-01JK47GVDMWMGPH8MQ0EW30Y25 ls /root
__pycache__  test00.py

Note that your executed command will terminate immediately once your Container has finished running.

By default, commands will be run within a pseudoterminal (PTY), but this can be disabled with the --no-pty flag.

Live container profiling

When a container or input is seemingly stuck or not making progress, you can use the Modal web dashboard to find out what code that’s executing in the container in real time. To do so, look for Live Profiling in the Containers tab in your function dashboard.

Debugging Container Images

You can also launch an interactive shell in a new Container with the same environment as your Function. This is handy for debugging issues with your Image, interactively refining build commands, and exploring the contents of Volumes and NetworkFileSystems.

The primary interface for accessing this feature is the modal shell CLI command, which accepts a Function name in your App (or prompts you to select one, if none is provided), and runs an interactive command on the same image as the Function, with the same Secrets and NetworkFileSystems attached as the selected Function.

The default command is /bin/bash, but you can override this with any other command of your choice using the --cmd flag.

Note that modal shell [filename].py does not attach a shell to a running Container of the Function, but instead creates a fresh instance of the underlying Image. To attach a shell to a running Container, use modal shell [container-id] instead.

Live updating

Hot reloading with modal serve

Modal has the command modal serve <filename.py>, which creates a loop that live updates an App when any of the supporting files change.

Live updating works with web endpoints, syncing your changes as you make them, and it also works well with cron schedules and job queues.

import modal

app = modal.App(image=modal.Image.debian_slim().pip_install("fastapi"))


@app.function()
@modal.fastapi_endpoint()
def f():
    return "I update on file edit!"


@app.function(schedule=modal.Period(seconds=5))
def run_me():
    print("I also update on file edit!")

If you edit this file, the modal serve command will detect the change and update the code, without having to restart the command.

Observability

Each running Modal App, including all ephemeral Apps, streams logs and resource metrics back to you for viewing.

On start, an App will log a dashboard link that will take you its App page.

$ python3 main.py
✓ Initialized. View app page at https://modal.com/apps/ap-XYZ1234.
...

From this page you can access the following:

• logs, both from your application and system-level logs from Modal
• compute resource metrics (CPU, RAM, GPU)
• function call history, including historical success/failure counts

Debug logs

You can enable Modal’s client debug logs by setting the MODAL_LOGLEVEL environment variable to DEBUG. Running the following will show debug logging from the Modal client running locally.

MODAL_LOGLEVEL=DEBUG modal run hello.py

To enable debug logs in the Modal client running in the remote container, you can set MODAL_LOGLEVEL using a Modal Secret.

@app.function(secrets=[modal.Secret.from_dict({"MODAL_LOGLEVEL": "DEBUG"})])
def f():
    print("Hello, world!")

Client tracebacks

To see a traceback (a.k.a stack trace) for a client-side exception, you can set the MODAL_TRACEBACK environment variable to 1.

MODAL_TRACEBACK=1 modal run my_app.py

We encourage you to report cases where you need to enable this functionality, as it’s indication of an issue in Modal.